The aim of this study was to analyse spatial and temporal homogeneity and trends in seasonal and annual precipitation and their fluctuations during 1957–2016 in Iran. For testing homogeneity, the Pettitt‐Whitney–Mann, the Standard Normal Homogeneity or Alexandersson's SNHT, Buishand's and the Von Neumann tests were used and for trend analysis, Mann‐Kendall and Sequential Mann‐Kendall tests were used. Homogeneity tests showed that most of the seasonal and annual precipitation time series were homogeneous and the change point was detected only at a few stations. Results indicated that in general, there was an upward trend during 1957–1986, followed by a significant downward trend during 1987–2016. The sequential Mann‐Kendall test detected several possible change points over time, although most of them were found statistically non‐significant at 95% confidence level. Upward and downward trends started in annual and seasonal precipitation after 1960 and 1990, respectively, at most stations, except in spring. In spring, an upward trend started after 1990 at some stations which showed a shift in precipitation from winter to spring. Also, the Sen's slope estimator indicated a higher downward trend in the northern parts of Iran. Two findings are worthy of note based on the results of this study. First, in general, a significant downward trend occurred in the whole country after1990. Second, a shift in precipitation from winter to spring was detected at some stations in different homogeneous regions.
Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Also, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.
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